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Monday, June 16, 2014

For those risk analysts out there using Monte Carlo in their analysis, have you ever wondered why the industry standard for simulation sample sizes in Monte Carlo is set at five thousand iterations?

So many Monte Carlo systems I see in use today run a standard five thousand simulations but why five thousand, why not ten thousand, why not five thousand and one?

How many samples should we have in our simulation sample size and when is the number of iterations insignificant? To be concise, if you were to add another sample to your Monte Carlo simulation, when doesn't it make a difference to the final result?

Saturday, June 14, 2014

Recent investigative journalism has turned out some pretty horrifying developments and realizations at the Fukushima Daiichi Nuclear Facility ... The video from Vice is nothing less than deeply concerning.

Friday, June 6, 2014

So to follow up on Part 1 of our Key Risk Indicator network or system which can be found here [LINK], perhaps the most important consideration we should ponder on is what do we actually do with the KRI data we capture?

In reality, why bother tracking Key Risk Indicators if we aren't going to do anything with them? Yet, so many risk managers do go through this very exercise without bringing it to full conclusion.

In this article I would like to describe at a top level what we can use our KRI data for and outline what holds us back from that objective.

Wednesday, June 4, 2014

Over a typical month a lot of risk practitioners in my network pose various technical questions to me. Today is no different but this month we certainly have an interesting query that goes along the following lines:

"I am creating a data model for KRIs and Op Risk Loss Events and would be curious to know how the metadata model and tables could work, how can I simulate or model Key Risk Indicators?" | US Banker

A good question without any doubt and from what I observe in general risk management practice, Key Risk Indicators are rarely modeled in coherent manner. Let's address the database design first, then we can investigate various ways in which Key Risk Indicators can be modeled.

Author

Martin Davies is a risk framework architect with strong domain knowledge across a diverse set of risk fraternities, a background in banking front-to-back and the ability to articulate business requirements into functional information technology concepts. He is focused on structured products for emerging markets and works with several tier one banks, regulators and brokerages across South East Asia.